Badea, Madalina C.

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  • Badea, Madalina C. (2)
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Author's Bibliography

Second-Order Adjoint Sensitivity and Uncertainty Analysis of a Heat Transport Benchmark Problem-II: Computational Results Using G4M Reactor Thermal-Hydraulic Parameters

Cacuci, Dan G.; Ilić, Milica; Badea, Madalina C.; Fang, Ruixian

(Amer Nuclear Soc, La Grange Pk, 2016)

TY  - JOUR
AU  - Cacuci, Dan G.
AU  - Ilić, Milica
AU  - Badea, Madalina C.
AU  - Fang, Ruixian
PY  - 2016
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2415
AB  - This work presents numerical results for the second-order sensitivities of the temperature distributions in a paradigm benchmark problem modeling heat transport in a reactor fuel rod and the surrounding coolant channel. The development of this benchmark problem was originally motivated by the need to very the numerical results for the first-order sensitivities produced by the FLUENT Adjoint Solver for the G4M Reactor preconceptual design and for a test section designed to investigate thermal-hydraulic phenomena of importance to the safety considerations for this reactor. The relative sensitivities computed using the FLUENT Adjoint Solver had significantly large values, of order unity, thereby motivating the need to investigate the impact of nonlinearities, the bulk of which are quantified by the responses' second-order sensitivities. However, the current FLUENT Adjoint Solver cannot compute second-order sensitivities, which in turn motivated the derivation of these sensitivities for the heat transport benchmark problem by using the recently developed second-order adjoint sensitivity analysis methodology. The numerical results obtained in this work used thermal-hydraulic parameters having mean values and standard deviations typical of the conditions found in the preliminary conceptual design of the G4M Reactor. These results show that the contributions of the second-order sensitivities to the expected values of the temperature distributions within the rod, on the rod's surface, and in the coolant are  lt 1% of the corresponding computed nominal values. Similarly, the contributions of the second-order sensitivities to the standard deviations of the temperature distributions within the rod, on the rod's surface, and in the coolant are also 1%, or less, of the corresponding contributions stemming from the first-order sensitivities, to the respective total standard deviations (uncertainties). These results justify the use of first-order sensitivities for computing expected uncertainties in the temperature distributions within the benchmark problem and, hence, mutatis mutandis, for the test section and G4M Reactor design. On the other hand, the most important impact of the second-order sensitivities is the positive skewnesses they induce in the temperature distributions within the rod, on the rod's surface, and in the coolant. This implies that all three temperature distributions, particularly in the heated rod, are non-Gaussian, asymmetric, and skewed toward temperatures higher than the respective mean temperatures.
PB  - Amer Nuclear Soc, La Grange Pk
T2  - Nuclear Science and Engineering
T1  - Second-Order Adjoint Sensitivity and Uncertainty Analysis of a Heat Transport Benchmark Problem-II: Computational Results Using G4M Reactor Thermal-Hydraulic Parameters
EP  - 38
IS  - 1
SP  - 22
VL  - 183
DO  - 10.13182/NSE15-80
ER  - 
@article{
author = "Cacuci, Dan G. and Ilić, Milica and Badea, Madalina C. and Fang, Ruixian",
year = "2016",
abstract = "This work presents numerical results for the second-order sensitivities of the temperature distributions in a paradigm benchmark problem modeling heat transport in a reactor fuel rod and the surrounding coolant channel. The development of this benchmark problem was originally motivated by the need to very the numerical results for the first-order sensitivities produced by the FLUENT Adjoint Solver for the G4M Reactor preconceptual design and for a test section designed to investigate thermal-hydraulic phenomena of importance to the safety considerations for this reactor. The relative sensitivities computed using the FLUENT Adjoint Solver had significantly large values, of order unity, thereby motivating the need to investigate the impact of nonlinearities, the bulk of which are quantified by the responses' second-order sensitivities. However, the current FLUENT Adjoint Solver cannot compute second-order sensitivities, which in turn motivated the derivation of these sensitivities for the heat transport benchmark problem by using the recently developed second-order adjoint sensitivity analysis methodology. The numerical results obtained in this work used thermal-hydraulic parameters having mean values and standard deviations typical of the conditions found in the preliminary conceptual design of the G4M Reactor. These results show that the contributions of the second-order sensitivities to the expected values of the temperature distributions within the rod, on the rod's surface, and in the coolant are  lt 1% of the corresponding computed nominal values. Similarly, the contributions of the second-order sensitivities to the standard deviations of the temperature distributions within the rod, on the rod's surface, and in the coolant are also 1%, or less, of the corresponding contributions stemming from the first-order sensitivities, to the respective total standard deviations (uncertainties). These results justify the use of first-order sensitivities for computing expected uncertainties in the temperature distributions within the benchmark problem and, hence, mutatis mutandis, for the test section and G4M Reactor design. On the other hand, the most important impact of the second-order sensitivities is the positive skewnesses they induce in the temperature distributions within the rod, on the rod's surface, and in the coolant. This implies that all three temperature distributions, particularly in the heated rod, are non-Gaussian, asymmetric, and skewed toward temperatures higher than the respective mean temperatures.",
publisher = "Amer Nuclear Soc, La Grange Pk",
journal = "Nuclear Science and Engineering",
title = "Second-Order Adjoint Sensitivity and Uncertainty Analysis of a Heat Transport Benchmark Problem-II: Computational Results Using G4M Reactor Thermal-Hydraulic Parameters",
pages = "38-22",
number = "1",
volume = "183",
doi = "10.13182/NSE15-80"
}
Cacuci, D. G., Ilić, M., Badea, M. C.,& Fang, R.. (2016). Second-Order Adjoint Sensitivity and Uncertainty Analysis of a Heat Transport Benchmark Problem-II: Computational Results Using G4M Reactor Thermal-Hydraulic Parameters. in Nuclear Science and Engineering
Amer Nuclear Soc, La Grange Pk., 183(1), 22-38.
https://doi.org/10.13182/NSE15-80
Cacuci DG, Ilić M, Badea MC, Fang R. Second-Order Adjoint Sensitivity and Uncertainty Analysis of a Heat Transport Benchmark Problem-II: Computational Results Using G4M Reactor Thermal-Hydraulic Parameters. in Nuclear Science and Engineering. 2016;183(1):22-38.
doi:10.13182/NSE15-80 .
Cacuci, Dan G., Ilić, Milica, Badea, Madalina C., Fang, Ruixian, "Second-Order Adjoint Sensitivity and Uncertainty Analysis of a Heat Transport Benchmark Problem-II: Computational Results Using G4M Reactor Thermal-Hydraulic Parameters" in Nuclear Science and Engineering, 183, no. 1 (2016):22-38,
https://doi.org/10.13182/NSE15-80 . .
15
13

A Heat Conduction and Convection Analytical Benchmark for Adjoint Solution Verification of Computational Fluid Dynamics Codes Used in Reactor Design

Cacuci, Dan G.; Fang, Ruixian; Ilić, Milica; Badea, Madalina C.

(Amer Nuclear Soc, La Grange Pk, 2016)

TY  - JOUR
AU  - Cacuci, Dan G.
AU  - Fang, Ruixian
AU  - Ilić, Milica
AU  - Badea, Madalina C.
PY  - 2016
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2406
AB  - This work presents a heat transport benchmark problem when modeling the steady-state radial conduction in a fuel rod coupled to the axial heat convection in a coolant surrounding the rod and flowing along it. This benchmark problem admits exact analytical solutions for the spatially dependent temperature distributions within the rod and the surrounding coolant. The adjoint sensitivity analysis methodology (ASAM) is applied to compute the analytical expressions of the adjoint state functions for this benchmark problem. In turn, these adjoint state functions are used to compute exactly the first-order sensitivities of the various temperature distributions to the benchmark's thermal-hydraulics parameters. Locations of particular importance are those where the rod, the rod surface, and the coolant temperatures attain their maxima. The analytical expressions of the benchmark sensitivities thus obtained are subsequently used to compute numerical values of the sensitivities of the various temperature distributions that would arise in the preliminary design of the G4M Reactor to thermal-hydraulics parameters characteristic of this reactor. The exact benchmark sensitivities are used for verifying the numerical results produced by the FLUENT Adjoint Solver, a code that has been used for computing thermal-hydraulics processes within the G4M Reactor. This solution verification process indicates that the current FLUENT Adjoint Solver cannot compute any sensitivities for the temperature distribution within the solid rod. However, the FLUENT Adjoint Solver is capable of computing the sensitivities of fluid temperatures to boundary parameters (e.g., boundary temperature, boundary velocity, and boundary pressure), but yields accurate results only for the sensitivities of the fluid outlet temperature and the maximum rod surface temperature to the inlet temperature and inlet velocity, respectively. Even for these sensitivities, the FLUENT Adjoint Solver typically needed over 20 000 iterations to converge to the correct solution. In fact, if the exact sensitivity results had not been known a priori, employment of a user-defined iteration-stopping criterion would have likely produced an erroneous result, which would have been noticed by the user only if the user had had the foresight of computing the respective sensitivities independently, via finite-differences using FLUENT recomputations. Several other important sensitivities, including sensitivities to the boundary heat transfer coefficient and sensitivities to material properties (thermal conductivity and specific heat), cannot be obtained from the current FLUENT postprocessing output. Ideally, the solution verification of the adjoint functions produced by the FLUENT Adjoint Solver would be performed by directly comparing these to the exact expressions of the adjoint functions for the benchmark problem. Such a direct comparison and, hence, a direct solution verification of the FLUENT Adjoint Solver, is currently not possible, because the current FLUENT Adjoint Solver does not provide access to the adjoint functions it computes. Therefore, the results produced by the FLUENT Adjoint Solver can only be verified indirectly, by comparing temperature sensitivities computed using the FLUENT Adjoint Solver to the exact results obtained from the analytical expression of the corresponding benchmark sensitivities. This situation further underscores the need for developing additional thermal-hydraulics benchmark problems that admit exact solutions.
PB  - Amer Nuclear Soc, La Grange Pk
T2  - Nuclear Science and Engineering
T1  - A Heat Conduction and Convection Analytical Benchmark for Adjoint Solution Verification of Computational Fluid Dynamics Codes Used in Reactor Design
EP  - 480
IS  - 4
SP  - 452
VL  - 182
DO  - 10.13182/NSE15-69
ER  - 
@article{
author = "Cacuci, Dan G. and Fang, Ruixian and Ilić, Milica and Badea, Madalina C.",
year = "2016",
abstract = "This work presents a heat transport benchmark problem when modeling the steady-state radial conduction in a fuel rod coupled to the axial heat convection in a coolant surrounding the rod and flowing along it. This benchmark problem admits exact analytical solutions for the spatially dependent temperature distributions within the rod and the surrounding coolant. The adjoint sensitivity analysis methodology (ASAM) is applied to compute the analytical expressions of the adjoint state functions for this benchmark problem. In turn, these adjoint state functions are used to compute exactly the first-order sensitivities of the various temperature distributions to the benchmark's thermal-hydraulics parameters. Locations of particular importance are those where the rod, the rod surface, and the coolant temperatures attain their maxima. The analytical expressions of the benchmark sensitivities thus obtained are subsequently used to compute numerical values of the sensitivities of the various temperature distributions that would arise in the preliminary design of the G4M Reactor to thermal-hydraulics parameters characteristic of this reactor. The exact benchmark sensitivities are used for verifying the numerical results produced by the FLUENT Adjoint Solver, a code that has been used for computing thermal-hydraulics processes within the G4M Reactor. This solution verification process indicates that the current FLUENT Adjoint Solver cannot compute any sensitivities for the temperature distribution within the solid rod. However, the FLUENT Adjoint Solver is capable of computing the sensitivities of fluid temperatures to boundary parameters (e.g., boundary temperature, boundary velocity, and boundary pressure), but yields accurate results only for the sensitivities of the fluid outlet temperature and the maximum rod surface temperature to the inlet temperature and inlet velocity, respectively. Even for these sensitivities, the FLUENT Adjoint Solver typically needed over 20 000 iterations to converge to the correct solution. In fact, if the exact sensitivity results had not been known a priori, employment of a user-defined iteration-stopping criterion would have likely produced an erroneous result, which would have been noticed by the user only if the user had had the foresight of computing the respective sensitivities independently, via finite-differences using FLUENT recomputations. Several other important sensitivities, including sensitivities to the boundary heat transfer coefficient and sensitivities to material properties (thermal conductivity and specific heat), cannot be obtained from the current FLUENT postprocessing output. Ideally, the solution verification of the adjoint functions produced by the FLUENT Adjoint Solver would be performed by directly comparing these to the exact expressions of the adjoint functions for the benchmark problem. Such a direct comparison and, hence, a direct solution verification of the FLUENT Adjoint Solver, is currently not possible, because the current FLUENT Adjoint Solver does not provide access to the adjoint functions it computes. Therefore, the results produced by the FLUENT Adjoint Solver can only be verified indirectly, by comparing temperature sensitivities computed using the FLUENT Adjoint Solver to the exact results obtained from the analytical expression of the corresponding benchmark sensitivities. This situation further underscores the need for developing additional thermal-hydraulics benchmark problems that admit exact solutions.",
publisher = "Amer Nuclear Soc, La Grange Pk",
journal = "Nuclear Science and Engineering",
title = "A Heat Conduction and Convection Analytical Benchmark for Adjoint Solution Verification of Computational Fluid Dynamics Codes Used in Reactor Design",
pages = "480-452",
number = "4",
volume = "182",
doi = "10.13182/NSE15-69"
}
Cacuci, D. G., Fang, R., Ilić, M.,& Badea, M. C.. (2016). A Heat Conduction and Convection Analytical Benchmark for Adjoint Solution Verification of Computational Fluid Dynamics Codes Used in Reactor Design. in Nuclear Science and Engineering
Amer Nuclear Soc, La Grange Pk., 182(4), 452-480.
https://doi.org/10.13182/NSE15-69
Cacuci DG, Fang R, Ilić M, Badea MC. A Heat Conduction and Convection Analytical Benchmark for Adjoint Solution Verification of Computational Fluid Dynamics Codes Used in Reactor Design. in Nuclear Science and Engineering. 2016;182(4):452-480.
doi:10.13182/NSE15-69 .
Cacuci, Dan G., Fang, Ruixian, Ilić, Milica, Badea, Madalina C., "A Heat Conduction and Convection Analytical Benchmark for Adjoint Solution Verification of Computational Fluid Dynamics Codes Used in Reactor Design" in Nuclear Science and Engineering, 182, no. 4 (2016):452-480,
https://doi.org/10.13182/NSE15-69 . .
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